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Optimal node deployment strategy for wireless sensor networks based on dynamic ant colony algorithm

机译:基于动态蚁群算法的无线传感器网络最优节点部署策略

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Sensor networks node deployment has long been a key problem in the research of wireless sensor networks. In order to reduce the cost of sensor deployment, this paper has proposed an optimised strategy for wireless sensor networks node deployment on the basis of dynamic ant colony algorithm, aiming at solving the problem of slow evolution and falling into local optimal solution frequently. The novel algorithm, DACA, features the integration of dynamic heuristic factor, expectations heuristic factor, dynamic evaporation factor, the optimal pheromone global updating strategy and the worst pheromone global updating strategy to improve ant colony algorithm. Then greedy strategy is introduced according to distribution of monitored nodes to make the algorithm more robust to environment changes. A large number of simulation results have proved the effectiveness of this algorithm and showed that the novel algorithm reduces the number of deployed nodes in the network for guaranteed connectivity and coverage.
机译:传感器网络节点部署一直是无线传感器网络研究中的关键问题。为了降低传感器部署的成本,本文提出了一种基于动态蚁群算法的无线传感器网络节点部署优化策略,旨在解决演进缓慢,经常陷入局部最优解的问题。新颖的算法DACA具有动态启发式因子,期望启发式因子,动态蒸发因子,最优信息素全局更新策略和最差信息素全局更新策略的集成,以改进蚁群算法。然后根据被监视节点的分布引入贪婪策略,使算法对环境的变化更加鲁棒。大量的仿真结果证明了该算法的有效性,并表明该新算法减少了网络中已部署节点的数量,从而确保了连接性和覆盖范围。

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